This invention relates to the field of cardiac resuscitation, and in particular to devices for assisting rescuers in performing chest compression during cardio-pulmonary resuscitation (CPR). Chest compression during CPR is used to mechanically support circulation in subjects with cardiac arrest, by maintaining blood circulation and oxygen delivery until the heart is restarted. The victim's chest is compressed by the rescuer, ideally at a rate and depth of compression in accordance with medical guidelines, e.g., the American Heart Association (AHA) guidelines. One key step for creating blood flow through the heart is to release the chest adequately after each chest compression. The chest should be released sufficiently to create a negative pressure in the chest, to facilitate venous filling of the heart and increased blood flow upon the next chest compression. If the chest is not released adequately, a positive thoracic pressure will remain which will hinder venous return and right atrial filling. Other key CPR parameters are maximal velocity of compression, compression depth, and average velocity. Compression depth and average velocity, together, provide good indication of potential blood flow volume. Maximal velocity of compression is an important factor in proper mitral valve closure and higher blood flow volume.
Sensors have been suggested for detecting the depth of chest compression. An accelerometer (with its output integrated to estimate depth) was disclosed, for example, in Freeman U.S. application Ser. No. 09/794,320, U.S. Pat. No. 6,306,107 and U.S. Pat. No. 6,390,996. Force (pressure) sensors were disclosed, for example, in Groenke U.S. Pat. No. 6,125,299. Force sensors provided no way of determining absolute displacement, as the compliance of the thoracic cage varies considerably from person to person. Accelerometers do not provide an indication of whether or not the chest is being released. They calculate displacement by double integration, which can result in a significant DC offset. U.S. Pat. No. 6,306,107 attempted to address the DC offset problem by incorporating a force sensor as a switch to indicate onset and conclusion of compression. The prior art has also employed mechanical pressure gauges to indicate to the rescuer the amount of force or pressure being applied to the chest. But these prior art uses of an accelerometer and/or force sensor have not provided a good solution to providing the rescuer with useful feedback as to whether the chest has been sufficiently released. Differences in compliance of the thoracic cage from one individual to another means that each individual will generally be able to support different amounts of force on the sternum without significant displacement occurring.
Increasingly, automated external defibrillators (AEDs) are used by rescuers treating victims of cardiac arrest for the delivery of defibrillatory shocks with the minimum of delay. The algorithms contained in the currently-available AEDs call for ‘hands off’ periods during which electrocardiographic (ECG) analysis is performed by the device and the rescuer withholds compressions. Compressions must be withheld because the accuracy of current rhythm analysis algorithms in AEDs is severely degraded by the artifact induced by the chest compressions. These AEDs also call for the rescuer to check for pulse or for signs of circulation during which time no compressions are performed. It has been shown in several studies that interruptions in the performance of chest compressions of as short a time as 20 seconds can dramatically reduce the probability of the return of spontaneous circulation (ROSC), a key survival measure. Other studies have also shown that the minimum amount of time required for the ‘hands off’ period is 20 seconds. There is therefore a need for the ability of AEDs to perform rhythm analysis while the rescuer continues with the chest compressions uninterrupted.
Resuscitation treatments for patients suffering from cardiac arrest generally include clearing and opening the patient's airway, providing rescue breathing for the patient, and applying chest compressions to provide blood flow to the victim's heart, brain and other vital organs. If the patient has a shockable heart rhythm, resuscitation also may include defibrillation therapy. The term basic life support (BLS) involves all the following elements: initial assessment; airway maintenance; expired air ventilation (rescue breathing); and chest compression. When all three (airway breathing, and circulation, including chest compressions) are combined, the term cardiopulmonary resuscitation (CPR) is used.
Current automated ECG rhythm analysis methods interrupt cardiopulmonary resuscitation (CPR) to avoid artifacts in the ECG resulting from chest compressions. Long interruptions of CPR have been shown to result in higher failure rate of resuscitation. Studies have reported that the discontinuation of precordial compression can significantly reduce the recovery rate of spontaneous circulation and the 24-hour survival rate. Y. Sato, M H. Weil, S. Sun, W. Tang, J. Xie, M. Noc, and J. Bisera, Adverse effects of interrupting precordial compression during cardiopulmonary resuscitation, Critical Care Medicine, Vol. 25(5), 733-736 (1997). Yu et al., 2002. Circulation, 106, 368-372 (2002), T. Eftestol, K. Sunde, and PA. Steen, Effects of Interrupting Precordial Compressions on the Calculated Probability of Defibrillation Success During Out-of-Hospital Cardiac Arrest, Circulation, 105, 2270-2273, (2002).
Management of breathing is another important aspect of the CPR process. Typical methods of monitoring breathing employ some form of impedance pneumography which measure and track changes in the transthoracic impedance of the patient. Currently, however, chest compressions result in significant artifact on the impedance signals, resulting in impedance-based pneumographic techniques as unreliable indicators of lung volume during chest compressions.
Adaptive filters have been attempted as a way of removing chest-compression artifacts in the ECG signal. S O. Aase, T. Eftestol, J H. Husoy, K. Sunde, and PA. Steen, CPR Artifact Removal from Human ECG Using Optimal Multichannel Filtering, IEEE Transactions on Biomedical Engineering, Vol. 47, 1440-1449, (2000). A. Langhelle, T. Eftestol, H. Myklebust, M. Eriksen, B T. Holten, P A. Steen, Reducing CPR Artifacts in Ventricular Fibrillation in Vitro. Resuscitation. March; 48(3):279-91 (2001). J H. Husoy, J. Eilevstjonn, T. Eftestol, S O. Aase, H Myklebust, and PA. Steen, Removal of Cardiopulmonary Resuscitation Artifacts from Human ECG Using an Efficient Matching Pursuit-Like Algorithm, IEEE Transactions on Biomedical Engineering, Vol 49, 1287-1298, (2002). H R. Halperin, and R D. Berger, CPR Chest Compression Monitor, U.S. Pat. No. 6,390,996 (2002). Aase et al. (2000) and Langhelle et al. (2001) used the compression depth and thorax impedance as reference signals for their adaptive filter. Husoy et al. (2002) extended this study by using a matching pursuit iteration to reduce the computational complexity; however, their results are usually computationally intensive, such as involving the calculation of a high order inverse filter. Halperin et al. (2002) proposed a frequency-domain approach using the auto- and the cross-spectrum of the signals and a time-domain approach using a recursive least square method for adaptive filtering the ECG signal. In both approaches, intensive computations are required.
There are numerous references available on adaptive filters. E.g., S. Haykin, Adaptive Filter Theory, Third Edition, Upper Saddle River, N.J., USA. Prentice-Hall, 1996